Light extinction tomography for measurement of ice crystals and other small particles

ABSTRACT

A tomography duct for wind tunnels includes a plurality of light sources and sensors displaced around a support structure. The light sources are cycled and sensor measurements are made from sensors opposite the light sources. Tomographic algorithms are used to determine an extinction map from the sensor measurements. The extinction map provides details about particles in a cross-section of the air flow through the tomography duct.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of application Ser. No. 16/126,558filed Sep. 10, 2018, which is a divisional of application Ser. No.15/170,715 filed Jun. 1, 2016, which is a continuation-in-part ofapplication Ser. No. 14/751,085 filed Jun. 25, 2015, which claims thebenefit of U.S. Provisional No. 62/017,143, filed Jun. 25, 2014, each ofwhich is herein incorporated by reference in its entirety.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with government support under contract#NNC112CA25C awarded by NASA/Glenn Research Center. The government hascertain rights in the invention.

STATEMENT REGARDING PRIOR DISCLOSURES BY AN INVENTOR OR JOINT INVENTOR

This subject matter of the present disclosure was presented to theAmerican Institute of Aeronautics and Astronautics on Jun. 25, 2013, inAAIA Paper No. 2013-2678, authored by Bencic, T J, Fagan, A F, VanZante, J F, Kirkegaard, J P, Rohler, D P, Maniyedath, A, and Izen, S H,and titled “Advanced Optical Diagnostics for Ice Crystal CloudMeasurements in the NASA Glenn Propulsion Systems Laboratory.”

TECHNICAL FIELD

The subject application teaches embodiments that relate generally to asystem of optical emitters and detectors configured to detect particledensity in a cross section flow between the emitters and detectors, andspecifically to an optical tomography system configured to detect ice orwater particle density in a cross section of a flow through a windtunnel.

SUMMARY

In an example embodiment, a system includes a support frame, a firstnumber of electromagnetic emitters, a second number of electromagneticdetectors, and a controller. The support frame surrounds partly or fullysurrounds a cavity through with a flow of air can pass without beinginterfered with substantially. The electromagnetic emitters aredisplaced along the support frame and are configured to emitelectromagnetic radiation toward the cavity and illuminated at least across-section of the flow of air. The electromagnetic detectors are alsodisplaced along the support frame, for example interleaved with theelectromagnetic emitters. The electromagnetic detectors care configuredto detect the electromagnetic radiation emitted from the electromagneticemitters. The controller is configured to cycle on-and-off each of theplurality of electromagnetic emitters in an illumination pattern. Duringeach on cycle, the controller acquires a measurement from a selectedgroup of electromagnetic detectors, for example those electromagneticdetectors situated approximately opposite the electromagnetic emitterthat is cycled on. From the acquired measurements, the controllerreconstructs an extinction map of the cross-section of the flow of airusing a tomography algorithm. The controller determines characteristicsof the particles in the flow of air from the reconstructed extinctionmap. The electromagnetic emitter can be an optical light emitter,monochromatic, spectrally filtered, an LED, a laser, or a light sourcecoupled to a fiber optic waveguides such as a fiber optic cable. Theelectromagnetic detector can be a pixel of a CCD or charge coupleddevice, one or more pixels of a CCD, or a fiber optic waveguide coupledto a portion of a CCD. The system can include a fiber coupler configuredto couple fiber optic waveguides such as fiber optic cables to a CCDsensor. The system can include collection widening optics for theemitters or detectors. They support frame can substantially surround thecavity. The support frame in conjunction with parts of the emitters anddetectors can form a tomography duct that is displaced in a wind tunnelbetween a sprayer and an engine under test. The wind tunnel generatesthe flow of air and the sprayer injects particles of water, supercooledwater, or ice into the flow of air. The tomography algorithm can includealgorithms such as an iterative reconstruction algorithm, a filteredbackprojection algorithm, a truncated singular value decompositionalgorithm, and diffraction tomographic reconstruction

In an example embodiment, a method includes measuring dark current of asensor element before the light source illuminates the tomography ductthrough which an air flow can be passed, and then emitting light from alight source across the tomography duct to a sensor element positionacross the tomography duct. On the sensor element, the impingingunextinguished light intensity can be measured and the tomographyalgorithm can be calibrated based on the dark current and measure of theunextinguished light intensity. A plurality of particles can be receivedinto the air flow and the sensor element then measures an extinguishedlight intensity based on the plurality of particles in the air flow. Thecalibrated tomography algorithm reconstructs an extinction map of across-section of the air flow based on the extinguished light intensity.The method can also include generating the air flow and injecting theplurality of particles into the air flow, which can be water droplets,supercooled water droplets, or ice particles. The method can includeadjusting the intensity of light emitted from the light source based onthe measured unextinguished light intensity. The method can includedetermining characteristics of the particles in the air flow based onthe reconstructed extinction map.

In an example embodiment, a method includes positioning a geometricsimulation component in a tomography duct of a wind tunnel, illuminatinglight sources displaced in tomography duct in an illumination pattern,and receiving light that is partially extinguished by one or morefeatures of the geometric simulation component by one or several sensordisplaced in the tomography duct. The method includes measuring theextinguished light intensity from selected sensor elements during eachof the illumination cycles in the illumination pattern, and based onmeasurements, reconstructing an extinction map using a tomographyalgorithm. The method includes comparing the reconstructed extinctionmap with an expected extinction map correlated with the geometricsimulation component, and adjusting the parameters of the tomographyalgorithm based on the comparison. The method can perform the adjustingin an iterative fashion by repeating some or all of the above steps. Thegeometric simulation component can be cross-shaped to test radialresolution of the tomography duct or ring-shaped to test angularresolution, and can include multiple concentric rings.

BACKGROUND

There have been over 200 documented cases of jet engine power lossevents during flight at high altitudes due to ingestion of iceparticles. The events typically occur at altitudes above 22,000 feet andnear deep convective systems, often in tropical regions. It isrecognized in the industry that supercooled liquid water does not existin large quantities at these high altitudes and therefore it is expectedthat the events are due to the ingestion of ice particles.

Based on this recent interest in ice particle threat to engines inflight, the NASA Glenn Research Center (GRC) installed the capability toproduce ice crystal and mixed phase water clouds in the PropulsionSystems Laboratory (PSL) Test Cell 3. The ice crystal cloud operationalparameters, developed with input from industry, were Median VolumetricDiameter (MVD) from 40 to 60 pm and Total Water Content (TWC) from 0.5to 9.0 g/m3. The PSL is currently the only engine test facility that cansimulate both altitude effects and an ice crystal cloud. It is acontinuous flow facility that creates the temperature and pressure inletconditions that propulsion systems experience in high-speed,high-altitude flight. Specifically for the icing system, the totaltemperature can be controlled between +45 to −60 F, pressure altitudefrom 4,000 to 40,000 feet (facility limit is 90,000 feet), and Mach from0.15 to 0.8 (facility limit is Mach 3.0).

Within this facility, there was a specific need to develop anon-intrusive system to measure the conditions of a cloud that enters anaircraft engine in the PSL. The system should (1) have the capability tobe operated remotely, (2) have minimal optical access, (3) no movingparts, (4) fast acquisition and (5) good resolution in a pipe that canstructurally support an aircraft engine in close proximity. An earlierstudy of this problem is described in “Application of the RadonTransform to Calibration of the NASA-Glenn Icing Research Wind Tunnel,”by Izen, S H, and Bencic, T J, in Contemporary Mathematics, Vol. 278,2001, pp. 147-166.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic drawing of a wind tunnel depicting the location ofa tomography duct relative to spray bars and an engine to be testedaccording to an embodiment of the disclosure.

FIG. 2 is a first view of a representation of a light extinctiontomography system installed in the NASA/Glenn Propulsion Systems Lab(PSL) at the tomography duct pipe exit according to an embodiment of thedisclosure.

FIG. 3 is a second view of the light extinction tomography system ofFIG. 2 illustrating cabling, laser sources, and optical detectorsaccording to an embodiment of the disclosure.

FIG. 4 is a schematic illustration of a rectangular icing researchtunnel.

FIG. 5 is a schematic illustration of the optical path for one lasersource and the detectors that receive useful signals from that sourceaccording to an embodiment of the disclosure.

FIG. 6A is an illustration of an ideal cross image.

FIG. 6B is an illustration of an ideal circles image.

FIG. 6C is an illustration of a cross image reconstructed by areconstruction algorithm according to an embodiment of the disclosure.

FIG. 6D is an illustration of a circles image reconstructed by areconstruction algorithm according to an embodiment of the disclosure.

FIG. 7A is an illustration of a detection system that includes a fibercoupling, associated optical fibers, and a camera element according toan embodiment of the disclosure.

FIG. 7B is an illustration of a fiber coupling for communicating lightto a camera element according to an embodiment of the disclosure.

FIG. 7C is an illustration of a sample data image of light collected by120 fibers of the detection system of FIG. 7A.

FIG. 8A is an illustration of the coverage provided by the projectionsof multiple light sources to detectors according to an embodiment of thedisclosure.

FIG. 8B is an illustration of a phantom image for use in demonstratingresolution quality differences between the center ring and the outerregions near the wall of the ring according to an embodiment of thedisclosure.

FIG. 8C is an illustration of resolution quality provided by thedetection system according to an embodiment of the disclosure.

FIG. 9 is an illustration of a tomography ring for measuring the densityof a water spray according to an embodiment of the disclosure.

DETAILED DESCRIPTION

The systems and methods disclosed herein are described in detail by wayof examples and with reference to the figures. It will be appreciatedthat modifications to disclosed and described examples, arrangements,configurations, components, elements, apparatuses, devices methods,systems, etc. can suitably be made and may be desired for a specificapplication. In this disclosure, any identification of specifictechniques, arrangements, etc. are either related to a specific examplepresented or are merely a general description of such a technique,arrangement, etc. Identifications of specific details or examples arenot intended to be, and should not be, construed as mandatory orlimiting unless specifically designated as such.

The systems and methods disclosed herein describe a light extinctiontomography system for use in detecting small liquid and solid (ice)water particles in various spray conditions. Visible light laser diodesare pulsed across an area of interest and the extinction or loss oflight intensity is measured at many different directions. The attenuatedlight projections across the field of view can be reconstructed to yieldan image of the particles that crossed the plane of light. This isanalogous to Computed Tomography (CT) in the medical imaging field inwhich slices of density through the body can generate images in theinterior. Although the disclosed system and method are described belowwith regard to visible light and water particles, the system and methodalso can be used with any suitable electromagnetic emitters anddetectors, and any suitable solid, fluid, or gas as would be understoodin the art.

The optical tomography system and method determines particle densitydetection. An example application considered here is the measurement ofice or water particle density in a cross section of a flow through awind tunnel, though other applications of the disclosure are alsocontemplated, for example as detailed below.

Turning to FIG. 1, in an embodiment a tomography duct 102 is integratedinto the walls 108 of a wind tunnel 100 so as not to impede or otherwiseinterfere with the air flow being measured. The tomography duct 102generally surrounds an internal space, or cavity, through which the airflows. In the wind tunnel, a sprayer such as spraybars 104 injectparticles into the air flow directed into an engine 106 that is undertest.

Turning now to FIGS. 2 and 3, in an embodiment a tomography duct 200includes a support frame 202, a set of light sources 204 that aredistributed around the support frame 202, and a set of optical detectors206 that are distributed around the support frame 202. The opticaltomography system also includes a control system (not shown) configuredto illuminate the light sources 204 in a desired illumination pattern, adetections system (not shown) configured to collect measurements fromthe optical detectors 206, a processing system (not shown) toreconstruct an extinction map from the measurements on the opticaldetectors 206. The control system (not shown) can be further configuredto provide a user interface and coordinate the illumination andmeasurement functions.

The support frame 202 is nominally circular to conform to the wall ofthe wind tunnel in which the frame is to be mounted. In some embodimentsthe support frame 202 becomes part of the wall of the wind tunnel. Inother embodiments, the support frame 202 can be inserted into the windtunnel and mounted within the wind tunnel. The system of the subjectdisclosure can be configured to work in any size wind tunnel providedthe support frame 202 is suitably scaled to the size of the wind tunnel.The support frame can be made of metal or other advanced structuralmaterials, as would be understood in the art. The light sources 204 andoptical detectors can be mounted onto the support frame 202. Forexample, the light sources 204 and optical detectors 206, along with anyoptics, can be flush mounted so as not to interfere with the flow beingmeasured.

Referring also to FIG. 4 in other embodiments a support frame 400 canhave a non-circular cross-section. For example, if the system of thesubject disclosure were to be used in the NASA-Glenn Icing ResearchTunnel, the support frame would have a rectangular cross-section similarto the support frame 400 shown in FIG. 4. The inner circle 402designates the region for which accurate imaging is desired and thesmall dots 404 represent candidate positions of light sources andoptical detectors according to an embodiment of the disclosure.

Refer now to the light sources 204 of FIGS. 2, 3, and 4. Because thepurpose of the system is to reconstruct particle density by measuringoptical extinction, bright light sources 204 are distributed around thesupport frame 202. The extinction along rays from each light source 204is measured on one or multiple optical detectors 206. In an embodiment,the light sources 204 are lasers, the illumination of which can beprecisely controlled by electrical signals. For example, as shown inFIG. 3, a laser controller 302 can pulse the laser light sources 204 inaccordance with an illumination pattern. Although lasers are used inthis embodiment, other intense light sources 204 could also be used aswould be understood in the art, including but not limited to lightemitting diodes. In an embodiment, one or more light sources 204 can beplaced in the controller 302 and coupled to the support frame 202 via anoptical waveguide such as a fiber optic cable. It can be desirable forthe extinction model to use monochromatic light. In an embodiment thelights sources 204 emit monochromatic light. In an embodiment spectralfilters can also be used with the light sources 204 to producemonochromatic light. As would be understood in the art, the system canuse any suitable frequency or frequencies of electromagnetic radiation,including but not limited to the optical light, infrared light,ultraviolet light, and so forth. Therefore the light sources 204 can beconfigured to emit electromagnetic radiation of one or more desiredfrequencies while the optical detectors 206 can be configured to detectelectromagnetic radiation of one or more desired frequencies.

In the present embodiment, it is desired to reconstruct particle densityalong a plane roughly transverse to the flow through the wind tunnel.Accordingly, it is desirable to focus the energy along an illuminationhalf-plane. For example, this can be accomplished with collimation, suchas is described in U.S. Pat. No. 6,184,989, filed Apr. 26, 1999 andtitled “Laser sheet tomography apparatus for flow field statistics”. Inthe present disclosure, the subject system provides an improved solutionthrough the use of optical elements configured to focus the light energyonto a half plane and disperse the energy as evenly as possible amongall directions from the source into the half-plane. In embodiments, dueto practical construction requirements, it can be necessary to shift thesources slightly off the plane of reconstruction. This configurationwill have the effect of reducing illumination onto detectors locatedclose to the source. This configuration should not have a major impacton reconstructed particle density.

The optical detectors 206 are sensors mounted along the support frame202 which are sensitive to light. The optical detectors 206 measure theoptical extinction along each path from the light sources 204 to theoptical detectors 206. In a configuration, the optical detectors 206have wide collection angles, and can include optics surrounding eachoptical detector 206 to widen the collection angle. While in anembodiment the optical detectors 206 on the support frame 202 can befiber optic cables with collection angle widening optics, otherdetection options will also work. For example suitable fiber opticwaveguides, including fiber optic cables, splitters, and so forth can beused, or individual detectors can be used. In an embodiment, each end ofthe fiber optic cables opposite that collecting the light from the lightsources 204 is mounted so as to point directly at a known location on acharge-coupled device (CCD) array. Thus, the light intensity on theoptical detector 206 can be measured by a CCD readout. As a practicalconsideration, the system of the present disclosure may have extrafibers not normally attached to the support frame 202 which can be usedas spares to replace defective optical detectors 206 attached to thesupport frame 202.

The optical detectors 206 are nominally distributed on the support frame202 in the plane of illumination. The optical detectors 206 may beslightly off the desired plane of reconstruction if practical mountingconstraints require it. In an embodiment, on a circular frame theoptical detectors 206 are evenly spaced and either completely orpartially interlaced with the light sources 204. The positions of thelight sources 204 and optical detectors 206, together, determine the“geometry” of the acquisition. In various embodiments, other geometriescan include features such as non-uniform spacing between either thelight sources 204, optical detectors 206, or both. In embodiments, thegeometries include light sources 204 and/or optical detectors 206 thatare slightly displaced from the measurement plane. In embodiments, thegeometries include evenly spaced optical detectors 206 shifted by afixed amount from the nominal interlaced geometry. One such embodimentis known as a quarter detector shift. In an embodiment, opticaldetectors 206 can be placed outside of the direct source illuminationplane in order to make measurements of scatter.

The measurement model has some similarity to that arising in medicalComputed Tomography (CT). However, our application has severalsignificant differences. In both medical applications and ours, thesources are in a ring outside the object and detectors are situated on afan across from the source. However, in medical applications, the objectof interest occupies a relatively small region about the center of thesource ring. In the present application, the detectors are situated onthe source ring, and the region of interest encompasses the entireinterior of the cross-section, (though the central region here is alsoof primary importance).

The particle density distribution is computed by measuring the opticalextinction along rays from the sources to the detectors. This data isreconstructed using tomographic algorithms to give a probability ofextinction at a given location in the cross section. Using extinctionmodels with expected particle size distributions, the material densitycan be recovered. In the present embodiment, the extinction model usessingle particle scattering. If in other applications, a single particlescattering model is not sufficient, diffraction tomographicreconstruction techniques can be used instead of the Radon inversionmethods used with the single scattering model.

To measure optical extinction with the preferred embodiment, three stepsare needed. First, the acquisition CCD is calibrated by measuring thedark current. That is, with no sources illuminated, data are acquired.This gives a measure of the detection signal in the absence ofstimulation, and allows the actual measurements to be calibrated.Typically, this does not need to be repeated frequently, as it is acharacteristic of the measurement CCD camera.

Next, data are acquired with no flow or particles present. This givesthe unextinguished light intensities. Finally, measurements are taken inthe presence of particles. The ratio of the Log of intensities (afterthe dark current is subtracted) gives the extinction along the opticalpaths from each source to each detector. These extinction data alongwith the source and detector “geometry” are input to the tomographicreconstruction algorithms. Specifically, the model can include detectorresponse characteristics related to (1) the incident angle of thesource-detector line relative to the detector surface and (2) thesource-detector distance.

While performing the flow absent measurement, various experimentalanomalies can be detected. For example, defective sources and/ordetectors can be identified. Also, detector gain levels can becalibrated to avoid saturation, or maximize signal-to-noise ratios.Relative sensitivity profiles can be determined and exploited inreconstruction algorithms. Modifications to reconstruction algorithms tohandle missing or unreliable data from known source-detector pairs canbe incorporated. Anomalies (such as a part from the test sectionprotruding into the measurement plane) during the flow-presentacquisition can also be detected and handled.

Refer also to FIG. 5. In order to perform an acquisition, the controlcircuitry pulses one source 502 at a time and can be performed undercomputer control. With the one source 502 active, each detector 504measures the light intensity from that source along the connecting ray506. In the preferred embodiment, this light is conducted to a specificregion on a CCD in a high precision CCD camera. The charge on the CCDsensor is read using the camera capabilities. The readout time from theCCD is the limiting factor in the timing of the source pulses. In anembodiment, by custom design of camera readout protocols, the readoutcan be restricted only to the regions of the CCD onto which fibers havebeen connected. This significantly reduces readout time, advantageouslyenabling a higher repetition rate.

The source pulse-readout sequence is repeated for each source on thesupport frame. After every source has been pulsed, sufficient data isavailable for the reconstruction engine to generate a particle densityprofile. The order in which each source is pulsed is referred to as thesource pattern. Example patterns can be simply pulsing adjacent sourcessequentially, or pulsing in a “star illumination pattern” and thensequentially using adjacent stars until all sources have been pulsed.For example, in an embodiment with 60 sources numbered sequentially from1 to 60, one five point star would be sources 1, 25, 49, 13, 37. So the“star” illumination pattern would be 1, 25, 49, 13, 37, 2, 26, 50, 14,38, 3, 27, 51, 15, 39, and so forth. Other source patterns can be usedas would be understood by one of ordinary skill in the art.

The star illumination patterns can be more robust with respect to timevariations in the flow during acquisition. The illumination pattern tobe used can be selected by the user and supported by the controllinghardware and software.

Tomographic reconstruction can be the recovery of a quantity from acollection of line integrals of the quantity or from a collection ofintegrals of the quantity over a narrow strip. The relevant quantity forthis application is liquid water content. For the particle sizesexpected in our embodiment and the optical path lengths across themeasurement section, the extinction of a beam of light passing throughthe spray will be proportional to the line integral or strip integral ofliquid water content along the optical path.

For a single scattering model, the measurements can be converted tosamples of the Radon transform of the extinction probability per unitlength. In the present embodiment, novel methods, with some similarityto those used in commercial CT scanners, are used to recover the profileof the extinction probability per unit length (and hence the particledensity). However, other methods specific to this application can alsobe used. For example, basis functions incorporating only low spatialfrequencies can be used instead of the pixel based basis functions, asthe expected particle densities do not have profiles with sharp edgesfor which high spatial frequencies are needed. Also, missing data can behandled by projection completion or interpolation. Alternatively,iterative reconstruction algorithms can also be applied. Note that somesuch algorithms which are not feasible in a medical setting areapplicable here due to the reduced size of the data set.

Because the reconstruction region extends to the source ring, thestandard reconstruction algorithms used in a medical setting must bemodified to avoid significant artifacts. Another difference is that oursample density is much lower, so the available resolution in thereconstruction of the spray will be relatively low. On the other hand,since the spray itself is not expected to have sharp transitions, thisis not expected to be a problem. Moreover, this a priori information canbe exploited by modeling the spray as a superposition of low spatialfrequency functions, such as Gaussian shaped blobs.

In addition, as a consequence of the implementations for some of thereconstruction methods discussed above, a method can be employed toprovide almost real-time temporal updates. After data for a full imagehas been obtained, each time a source has been pulsed as part of thenext acquisition, the data from that partial acquisition can replace thedata from the previous pulsing of the same source. Only the new dataneeds to be processed to obtain an updated image. This idea can beapplied to data obtained from any group of sources, such as a star inthe star illumination patterns.

As an alternative to the traditional medical-type reconstruction, analgorithm has been developed which incorporates this a priori knowledgeto reduce the computational complexity. It should be noted that thealternative algorithm does not scale well to the medical setting, but iswell suited for use with the sampling densities available here. In thisalgorithm, the measurements are simulated for each possible Gaussianblob. The acquired spray measurement is fit to a linear combination ofthe simulated blob measurements. The corresponding linear combination oflow spatial frequency functions is taken as the reconstructed image.This method is easily adapted to handle minor malfunctions in theacquisition system such as a dark source, or a dead detector.

In order to reduce streaking artifacts, the sampled data can beup-sampled from 120×60 to 480×240. This up-sampling preserves theoriginal bandwidth of the data. The reconstruction is based on thisoriginal bandwidth and does not improve the resolution, even though thereconstruction is performed on a finer grid. Although this method doeswell in the central ⅔ of the field of view, it is not as robust in theouter ring due to the uneven coverage of source-detector paths throughthe outer ring, and also because the filtered backprojection algorithmrelies on an approximation which is less valid at reconstruction pointsclose to the source ring.

For the rectangular frame as shown in FIG. 4, a different reconstructionmethod can be successfully used. The Truncated Singular ValueDecomposition (TSVD) algorithm is a well-known method for regularizingthe solution for the matrix equation, y=Rx.

In the context of the rectangular geometry, the column vector y holdsthe measured data, with each element corresponding to a source-detectorpair. Each element of the column vector x corresponds to the clouddensity at a position within the rectangular geometry. The matrix Rrepresents the integrals over each source detector pair which takes acloud distribution x to the measurement y.

Because the linear equation is typically both over or under constrained,it is solved by use of the pseudo-inverse, R⁺. The solution vectorx=R⁺y, is the vector x with minimum norm that also minimizes the size ofthe residual y−Rx.

Unfortunately, when R⁺ is ill-conditioned, meaning that some componentsin the data y will have a greatly magnified influence in the solution x,it is necessary to regularize R+ as noise in the measurements (random,system, or numerical) will be amplified in the solution, swamping thereconstruction. Regularization effectively removes this inordinateamplification. The TSVD algorithm limits the acceptable magnification byignoring the components in the data which would be unduly amplified inthe solution. There is a trade-off between reconstruction resolution andfidelity and noise amplification which is tuneable by selection of anoise amplification threshold.

The application of the TSVD algorithm involves a time consumingcomputation of the SVD (singular value decomposition) of the matrix R.This computation grows like the 4th power of the number of linear pixelsin the reconstructed image. Fortunately, the SVD only needs to becomputed once (offline), so it will not significantly impact cloudreconstructions.

Raw data and reconstructed density patterns can be archived. The subjectsystem can include a module for analysis of reconstructed densitypatterns. In particular, temporal averaging of density patterns isavailable (and also available in real time).

Referring now also to FIGS. 6A, 6B, 6C, and 6D, the subject system caninclude a simulator that has two (2) key capabilities. (1) Phantomobject data can be generated according to specified parameters. (2)Measurement data can be produced using a phantom object and a model ofthe measurement system.

The phantom object can include cloud components or geometric components.Cloud components are used, for example, to characterize the fidelityprovided by the measurement system and the reconstruction. Geometriccomponents are used, for example, to characterize the spatial resolutionof the measurement system and the reconstruction. In FIGS. 6A and 6B,geometric simulation components are shown. In FIG. 6A, a cross-shapedgeometric simulation component uses pins that are placed 2-inches apart,thus there is a 1-inch gap between each pin. The pins can be hollow asshown or solid. In FIG. 6B, a circles-shaped geometric simulationcomponent uses rings of pins where each ring is places so that thecircumferential gap is 1-inch between the 1-inch pins. The cross-shapedgeometric simulation component tests radial resolution and thecircles-shaped geometric simulation component will test angularresolution. FIG. 6C shows the result of reconstructing the cross-shapedgeometric simulation component and FIG. 6D shows the result ofreconstructing the circles-shaped geometric simulation component usingone embodiment of the reconstruction algorithm.

By specifying various parameters of the measurement system, thesimulator can be used to determine an effective hardware design. Thesimulator advantageously aids in the design of the reconstructionalgorithm and parameters.

Referring back to FIGS. 2, and 3, an embodiment of a light extinctiontomography system consists of 60 equally spaced laser diodes with sheetgenerating optics and diffusing elements providing >300 degree coveragearound the ring and 120 fiber optically coupled detection elementsmounted every 3 degrees around a 36-inch diameter ring. Each detectorutilizes a flashed opal input diffuser at the fiber entrance which iscoupled to the CCD camera for simultaneous sampling of all 120 channels.The diffuser allows coupling of the laser light into the fibers at avery wide input angle of approximately +/−85 degrees with respect to thefiber face. The diffusers greatly increase the acceptance angle of thefibers at the cost of allowing only a small amount of the incident lightto be coupled into the fiber. The laser diode sources are pulsedsequentially while the detectors acquire line-of-sight extinction datafor each laser pulse. A custom timing/triggering circuit was builtin-house and used to control the data acquisition. Referring now also toFIGS. 7A, 7B, and 7C, optical fibers and a detection system areillustrated. The optical fibers 702 are direct coupled to the CCD 704through a fiber optic faceplate 706, or fiber coupling. The imagedfibers are read out as a 5×5 pixel binned region of interest 708 in thecenter of the fiber which yields a pixel per fiber or a 120 pixel imageper sequential laser scan. A controller 710 is in data communicationwith the CCD 704 and receives the image. In an embodiment, thetiming/trigger circuit can be combined with the controller 710. Invarious embodiments, the controller 710 can perform any suitableoperation described above, including but not limited to the executingthe tomography algorithms. In other embodiments, individual controllerscan separately perform different operations.

Using the computed tomography algorithms discussed in the previoussection the extinction data is used to produce a plot of the relativewater content in the measurement plane with spatial resolution betterthan 1 inch over the central 75% of the measurement area.

Referring now to FIG. 8A, lines from several sources and thecorresponding projections to the detectors are illustrated. This givessome indication about the expected resolution as the area near the wallhas a minimal amount of line crossing in multiple directions. Referringnow to FIG. 8B, a resolution study was performed to determine theexpected resolution across the duct plane using simulated phantom dataof 1 inch circles. Referring now to FIG. 8C, a reconstruction wasperformed of the simulated line projection information. Thereconstruction of the 60 source, 120 detector configuration is shown inFIG. 8C illustrates the loss of resolution with increasing radialdistance from the center of the duct. The 1 inch circles are clearlyevident in the inner two rings which represent approximately a 12 inchdiameter. The third ring of circles from the center are now turned intoovals which shows a loss of angular resolution but each dot can still berecognized, this corresponds to a diameter of approximately 20 inches.The outermost dots are completely blended together at approximately a 30inch diameter. This study was performed using a high spatial frequencymodel because of the abrupt high contrast of the dots on the blackbackground. This high spatial resolution leads to reconstructionartifacts which can be ignored since the intent of the study is toconfirm the expected resolution and not to minimize the reconstructionnoise.

The subject system and method can be used as a particle densitydetection system for a number of suitable applications, including butnot limited to the following. In an embodiment, the system and methodcan be used to measure the density of ice or water particles inside awind tunnel in real time and provide an archival record of particledensity. In particular, spray patterns can be visualized. Anomalies inspray patterns, such as inoperative or malfunctioning nozzles or sprayhot spots, can be detected. The system and method can be used forengineering desired sprays and spray patterns.

In an embodiment, the system and method can be used as part of a windtunnel instrumentation, for example to provide feedback and control forspray settings, both automatic or manually with human intervention.

In an embodiment, the system and method can provide measurement of ageneral spray system such as paint or water, for example in anindustrial setting as illustrated in FIG. 9, which also possibly caninclude a control element.

In an embodiment, the system can be mounting in the intake of a jetengine to provide real time and archival records of flight conditions.Upon detection of dangerous icing conditions, a system could alert thepilot and/or adjust engine parameters to ensure safe operation.

In an embodiment, the system and method can be used to measureatmospheric particulate density, for example volcanic ash or from othersources of emissions.

In an embodiment, the system and method can be used to comparehistorical data for repeatability and to determine trends for sources,detectors and sprays, including individual nozzles.

In an embodiment, the system and method can be used for analyzing smokestack emissions. The frequencies used for the electromagnetic emitterscan be configured to absorption peaks of the effluents or particlesbeing detected.

While certain embodiments have been described, these embodiments havebeen presented by way of example only, and are not intended to limit thescope of the inventions. Indeed, the novel embodiments described hereinmay be embodied in a variety of other forms; furthermore, variousomissions, substitutions and changes in the form of the embodimentsdescribed herein may be made without departing from the spirit of theinventions. The accompanying claims and their equivalents are intendedto cover such forms or modifications as would fall within the spirit andscope of the inventions.

What is claimed is:
 1. A method, comprising: positioning a geometricsimulation component in a tomography duct of a wind tunnel; illuminatinga plurality of light sources displaced along the tomography duct in anillumination pattern; receiving, by at least a portion of a plurality ofsensor elements displaced along the tomography duct, light that is atleast partially extinguished by one or more features of the geometricsimulation component; measuring from one or more selected sensorelements an extinguished light intensity for each of a plurality ofillumination cycles in the illumination pattern; reconstructing, using atomography algorithm, an extinction map based at least in part on aplurality of measurements of extinguished light intensity; comparing thereconstructed extinction map with an expected extinction map for thegeometric simulation component; and adjusting parameters of thetomography algorithm based at least in part on comparison of thereconstructed extinction map and the expected extinction map.
 2. Themethod of claim 1, further comprising: iteratively adjusting theparameters of the tomography algorithm based at least in part onrepeating the reconstructing and comparing operations.
 3. The method ofclaim 1, wherein the geometric simulation component is a cross-shapedgeometric simulation component configured to test radial resolution ofthe tomography duct.
 4. The method of claim 1, wherein the geometricsimulation component is a ring-shaped geometric simulation componentconfigured to test angular resolution of the tomography duct.
 5. Themethod of claim 4, wherein the geometric simulation component furthercomprises: a plurality of concentric rings.